Photographic imaging service applications have been extended to include digital imaging technology. For Internet-based photographic service applications, a consumer is provided a means for displaying his/her digital images with the digital images residing on a remote computer. Typical scenarios for these Internet-based digital imaging applications include the viewing thumbnail versions of a collection of digital images, selection of a particular digital image for viewing, enhancement, and/or printing. While there exist many different methods for an Internet-based photographic service provider to receive payment for the service rendered, many have chosen to display advertisement messages on the consumer's display screen and collect payment not from the consumer, but from an advertisement client. At present, it is possible for the photographic service provider to perform directed advertisement if prior knowledge of the consumer in the form of a consumer profile is available. However, if no prior knowledge of the consumer is available, directed advertising is not possible. Furthermore, the consumer profile may not be up-to-date. Moreover, the profile may not account for some facets of a consumer's buying habits. If an employee of the photographic service provider were to view the consumer's photographs, the employee could make intelligent decisions as to which advertisement client would most likely desire directed advertisement to the particular consumer. Aside from issues of privacy of consumer photographs, the process of humans observing photographs and making directed advertising decisions is too costly for consideration. Research has shown that unrelated directed advertisements are often considered nuisance by the consumer while directed advertisement which relate to the interests of the consumer are considered desirable.
Digital imaging algorithms have for a long while been devised to analyze the content of digital images. In particular, the methods disclosed by Cullen et al. in U.S. Pat. No. 5,933,823, Ravela et al. in U.S. Pat. No. 5,987,456, and De Bonet et al. in U.S. Pat. No. 5,819,288 analyze digital images. In these digital imaging applications a database of digital images is maintained. For each digital image in the database a set of image features, expressed in mathematical form, are calculated. A query digital image is selected, usually initiated from the user of the digital imaging application, and compared to the digital images in the database. The same set of image features is calculated for the query digital image. A comparison between the calculated image features for the query digital image and the database digital images is performed and yields an image similarity value for each of the database digital images as a measure of overall similarity. The image similarity values are analyzed and the digital images with the highest image similarity values are displayed for the user.
While these digital image query applications are capable of analyzing digital images, none of the above mentioned disclosed methods relate the content of a set of consumer digital images to the likelihood of an advertisement client's desire to direct advertisement material to that particular consumer.